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Re. failed Travis build: happy to test this out in a separate branch/PR, but I think it can be solved by following the Conda instructions for installing it on Travis.
The error from the build:
The command "sudo -H conda init" failed and exited with 1 during .
From http://conda.pydata.org/docs/commands/conda-init.html:
WARNING: conda init is deprecated. The recommended way to manage pip installed conda is to use pip to manage the root environment and conda to manage new conda environments. Note that pip installing conda is not the recommended way for setting up your system. The recommended way for setting up a conda system is by installing Miniconda.
It is not time to merge this at all yet... What I want to discuss is mostly the workflow :)
On Thursday, September 15, 2016, Eliza Chang notifications@github.com wrote:
Re. failed Travis build: happy to test this out in a separate branch/PR, but I think it can be solved by following the Conda instructions for installing it on Travis http://conda.pydata.org/docs/travis.html.
The error from the build:
The command "sudo -H conda init" failed and exited with 1 during .
From http://conda.pydata.org/docs/commands/conda-init.html:
WARNING: conda init is deprecated. The recommended way to manage pip installed conda is to use pip to manage the root environment and conda to manage new conda environments. Note that pip installing conda is not the recommended way for setting up your system. The recommended way for setting up a conda system is by installing Miniconda.
— You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub https://github.com/simonsfoundation/inferelator_ng/pull/26#issuecomment-247361994, or mute the thread https://github.com/notifications/unsubscribe-auth/AMZwNH485xkJr7IQiMURmV1GOsxZD9bXks5qqWRLgaJpZM4J7uL- .
As promised, this is my first trial at creating a workflow for a multitask learning problem... I think the main thing to keep in mind is that the input for the inference step for each gene is a collection of design and response matrices, and the assumption is that sharing information between related datasets will be beneficial to network recovery. I think the idea for the meeting on Thursday is to figure out what is the best way to build a workflow for similar problems, since there are many possibilities for the inference step that one might wanna try. Also, I haven't tested the workflow substantially, so don't expect it to be running. I guess the idea is just to look at how the problem is structured and how to make it better. Thanks!